scholarly journals Essential Computer Vision Methods for Maximal Visual Quality of Experience on Augmented Reality

2016 ◽  
Vol 3 (2) ◽  
pp. 39-45
Author(s):  
Suwoong Heo ◽  
Hyewon Song ◽  
Jinwoo Kim ◽  
Anh-Duc Nguyen ◽  
Sanghoon Lee
Keyword(s):  
Computer Vision ◽  
Augmented Reality ◽  
Quality Of Experience ◽  
Visual Quality

ASSESSMENT OF THE QUALITY OF EXPERIENCE OF AUGMENTED REALITY APPLICATIONS WITH VIRTUAL ASSISTANTS

2021 ◽  
Author(s):  
М.А. МАКОЛКИНА ◽  
А.С. БОРОДИН ◽  
Б.О. ПАНЬКОВ
Keyword(s):  
Augmented Reality ◽  
Quality Of Experience ◽  
Augmented Reality Application

Рассмотрено применение виртуальных ассистентов при реализации услуг дополненной реальности (ДР). Разработано приложение ДР с виртуальным ассистентом и проведена оценка качества восприятия с помощью субъективных и объективных методов. The article discusses the use of virtual assistants in the implementation of augmented reality services. An augmented reality application with a virtual assistant was developed and the quality of the experience was assessed using subjective and objective methods.

scholarly journals A Quality of Experience assessment of haptic and augmented reality feedback modalities in a gait analysis system

PLoS ONE ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. e0230570 ◽  
Author(s):  
Thiago Braga Rodrigues ◽  
Ciarán Ó Catháin ◽  
Noel E. O’Connor ◽  
Niall Murray
Keyword(s):  
Augmented Reality ◽  
Gait Analysis ◽  
Quality Of Experience ◽  
Feedback Modalities ◽  
Analysis System

Application of Computer Vision Techniques for Exploiting New Video Coding Mechanisms

2018 ◽  
pp. 1864-1892
Author(s):  
Artur Miguel Arsenio
Keyword(s):  
Computer Vision ◽  
Image Quality ◽  
Video Coding ◽  
Quality Of Experience ◽  
Service Providers ◽  
End User ◽  
Application Service Providers ◽  
Application Service ◽  
Content Consumption

One of the main concerns for current multimedia platforms is the provisioning of content that provides a good Quality of Experience to end-users. This can be achieved through new interactive, personalized content applications, as well by improving the image quality delivered to the end-user. This chapter addresses these issues by describing mechanisms for changing content consumption. The aim is to give Application Service Providers (ASPs) new ways to allow users to configure contents according to their personal tastes while also improving their Quality of Experience, and to possibly charge users for such functionalities. The authors propose to employ computer vision techniques to produce extra object information, which further expands the range of video personalization possibilities on the presence of new video coding mechanisms1.

Application of Computer Vision Techniques for Exploiting New Video Coding Mechanisms

2013 ◽  
pp. 156-182 ◽  
Author(s):  
Artur Miguel Arsenio
Keyword(s):  
Computer Vision ◽  
Image Quality ◽  
Video Coding ◽  
Quality Of Experience ◽  
Service Providers ◽  
End User ◽  
Application Service Providers ◽  
Application Service ◽  
Content Consumption

One of the main concerns for current multimedia platforms is the provisioning of content that provides a good Quality of Experience to end-users. This can be achieved through new interactive, personalized content applications, as well by improving the image quality delivered to the end-user. This chapter addresses these issues by describing mechanisms for changing content consumption. The aim is to give Application Service Providers (ASPs) new ways to allow users to configure contents according to their personal tastes while also improving their Quality of Experience, and to possibly charge users for such functionalities. The authors propose to employ computer vision techniques to produce extra object information, which further expands the range of video personalization possibilities on the presence of new video coding mechanisms.

scholarly journals Quality of Experience (QoE)-Aware Fast Coding Unit Size Selection for HEVC Intra-prediction

2019 ◽  
Vol 11 (8) ◽  
pp. 175 ◽  
Author(s):  
Buddhiprabha Erabadda ◽  
Thanuja Mallikarachchi ◽  
Chaminda Hewage ◽  
Anil Fernando
Keyword(s):  
Video Coding ◽  
Real Time ◽  
Quality Of Experience ◽  
Visual Quality ◽  
Intra Prediction ◽  
Support Vector ◽  
Brute Force ◽  
Size Selection ◽  
Coding Unit

The exorbitant increase in the computational complexity of modern video coding standards, such as High Efficiency Video Coding (HEVC), is a compelling challenge for resource-constrained consumer electronic devices. For instance, the brute force evaluation of all possible combinations of available coding modes and quadtree-based coding structure in HEVC to determine the optimum set of coding parameters for a given content demand a substantial amount of computational and energy resources. Thus, the resource requirements for real time operation of HEVC has become a contributing factor towards the Quality of Experience (QoE) of the end users of emerging multimedia and future internet applications. In this context, this paper proposes a content-adaptive Coding Unit (CU) size selection algorithm for HEVC intra-prediction. The proposed algorithm builds content-specific weighted Support Vector Machine (SVM) models in real time during the encoding process, to provide an early estimate of CU size for a given content, avoiding the brute force evaluation of all possible coding mode combinations in HEVC. The experimental results demonstrate an average encoding time reduction of 52.38%, with an average Bjøntegaard Delta Bit Rate (BDBR) increase of 1.19% compared to the HM16.1 reference encoder. Furthermore, the perceptual visual quality assessments conducted through Video Quality Metric (VQM) show minimal visual quality impact on the reconstructed videos of the proposed algorithm compared to state-of-the-art approaches.

Sign in / Sign up

Export Citation Format

Share Document